Ford Credit Europe's (FCE) Data and Analytics Solutions (DAS) team provides comprehensive data services to the organisation, including Data Governance & Lineage, Data Quality, Master Data Management, and the delivery of the FCE Data Strategy enabling self-service and analytics. This is a dynamic and evolving area of the FCE Business, leveraging new tools, processes, and technology to enable faster business access to greater insights required for European growth and regulatory compliance.
We're seeking a Data Specialist to join our team to develop robust data solutions for FCE and Ford Bank Germany (FBG). This role focuses on collaborating with customers to identify, document, and solve data needs, implementing semantic models within our data platforms, and creating data solutions that enable advanced analytics and future AI-powered tools for our business customers.
As part of our DAS transformation, you'll work closely with Data Engineering and Data Architecture teams to implement semantic models that translate complex banking data into accessible business insights while ensuring full regulatory compliance.
Essential Requirements
Data & Engineering Skills
1. SQL: Advanced querying, transformation, and performance optimisation
2. Python: Strong capability for data manipulation, analysis, and automation
3. Looker / LookML: Hands‑on experience building LookML models and dashboards
4. Power BI: Proficient in developing BI reports and analytics solutions
5. GCP: Experience with BigQuery and familiarity with wider GCP data tooling
6. Cloud Data Warehousing: Knowledge of cloud‑based storage and warehousing concepts
7. AI/ML Exposure: Basic understanding of machine learning concepts; willingness to learn BigQuery ML, AutoML, etc.
8. Git / GitHub: Proficient in version control for code and documentation
Data Management & Analytics
9. Semantic Modelling: Understanding of semantic layers, business definitions, and logical data structures
10. Data Quality: Knowledge of data validation, cleansing techniques, and QA processes
11. Business Intelligence: Ability to build self‑service analytics and reporting layers
12. Data Analysis: Capable of interpreting complex datasets to produce meaningful insights
Education
13. Degree: Bachelor’s degree in a data‑related discipline (preferred)
The Company is committed to diversity and equality of opportunity for all and is opposed to any form of less favourable treatment or harassment on the grounds of race, religion or belief, sex, marriage and civil partnership, pregnancy and maternity, age, sexual orientation, gender reassignment or disability
This position is based in Dunton, and it is expected the successful candidate will be able to attend the Dunton Campus for typically 4 days a week and remain flexible on the days they are required to attend the office according to business requirements.
As part of our pre-employment checks process, successful candidates will be required to undergo a criminal record check. This will be conducted in line with the Rehabilitation of Offenders Act 1974 and applied only to unspent convictions.
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